Mechanisms of drug action - we need to rethink our models

When we think about the mechanism of drug action we almost always look to the traditional sigmoidal log dose or log concentration response relationship.

Students are almost always befuddled by the fact that once you go into the clinics, hardly anyone ever refers to this fundamentally important relationship. It seems to be important only at lab benches and do not seem to apply in the clinical context. Part of the reason for this is few drugs exhibit a range of actions that span the entire range of that sigmoidal curve. Many drugs either just operate close to the Emax or are limited in getting close to Emax because of toxicity, or compensatory mechanisms. One other constraint is that the estimates of concentrations are poorly representative of the actual concentrations at the effector site. So often we are reduced to just looking at circulating (fluctuating) plasma concentrations (which are very distant from the effector site) or a very crude estimate of the administered dose.

One other problem is that our ideas of drug response mechanisms are heavily influenced by receptor binding models shaped by earlier studies of G-protein type membrane receptors. The simplistic model assumes easily reversible competitive binding to a receptor with almost immediate effects. More and more drugs nowadays do not operate that way.

Here is a list of the top 50 prescribed drugs (as listed by IMS in 2007).

Of these only a minority can be regarded as operating according to that model of drug action. If you consider that many clinically useful drugs (antiinfectives, anticancer, etc) work through mechanisms more related to irreversible cell kill type models, I think you can readily appreciate the inadequacy of that simplistic traditional concentration-response model of drug action.

Measures of efficacy

In the previous posts we had considered the optimization of warfarin dosages. The genotyping offers an added dimension to the optimization process, but may not be really cost effective. The warfarin problem is probably not a good example for predictive genotyping. This is because it already has a very good biomarker of clinical response - the INR (International Normalized Ratio). Most other drugs do not have good measures of clinical response. The absence of such measures of efficacy makes the optimization much more challenging.

Some drugs like warfarin allow direct measurement of the therapeutic efficacy. So for warfarin, it is the INR. For antihypertensive drugs, it could be the blood pressure response. For an antiasthmatic bronchodilator, it could be the airway relaxation, FEV1 for example. For an antidiabetic drug, it could easily be the blood glucose response. There are many other examples.

But for many therapeutic areas, the clinical response is much less directly quantifiable. For example, in the use of an antiepileptic drug, without a good surrogate measure of response, one is never really sure whether appropriate amounts of drug have been used. Likewise, for an antibiotic or a chemotherapeutic agent, the inappropriateness of the dosing regiment may not be recognized until it is too late.

For such situations, the availability of a 'surrogate' measure of response may be critical in patient care. One such surrogate measure is the measurement of circulating drug concentrations. Crude though it may be, getting the patient into a 'therapeutic range' may provide some guidance as to whether or not appropriate dosages have been used. Such an approach is sometimes referred to as the 'target concentration strategy'. There are however limitations to this method and it is not always applicable.

For the target concentration strategy to work, there must be evidence that circulating concentrations bear a good relationship to therapeutic outcome.

CYP4F2

The CYP4F2 is involved in the synthesis of a number of sterols and lipids. Because it was involved in the production of 20-hydroxyeicosatetraenoic acid (20-HETE), it was postulated to be involved in the pathophysiology of hypertension. It is now thought to be also involved in the breakdown of Vit K1. Correspondingly, the V433M variant is thought to result in decreased breakdown of VitK1 and an leading an excess of VitK1, leading to relative warfarin resistance. Recent studies have suggested that the polymorphism contributes 1-2% of the variability in warfarin dosage requirements.

The frequency of the polymorphism in Caucasians and 'Asians' is approximately 30%. There isn't any more specific population frequencies than these, and I have no breakdown of Chinese, Malay and Indian frequncies.

Manny Pacquiao (a.k.a. Pac-man)

Sorry for the long silence.I haven't been sleeping .... just pretty busy thinking about lots of other things. Here's something for you to think about.

Manny Pacquiao (a.k.a. Pac-man). Small man punching above his weight and reach to victory against Ricky Hatton.

Much as I don't really like boxing as a sport because of the physical violence, when you watch a great boxer at his craft, it's really poetry in motion. Yes, there is beauty, even in violence.

But the real reason why I am posting about this here is to point this out as a dramatic example of human diversity. If you haven't watched the video, do try and watch it somewhere where it hasn't been taken down yet. :) Watch the man's hands. Literally fast as lightning. Hatton didn't have a chance.

Makes you wonder about what makes the muscles move so fast for this man.

Grapefruits and ....Pomelos

Few people in the west will know about pomelos. Apart from being a really yummy fruit, it is as potent as grapefruit in inhibiting CYP3A4, and MDR1 as well.

Here's my interpretation of the family tree of the pomelo and how it relates to the grapefruit.

Grapefruit, CYP3A4 and deep vein thrombosis

Here's an interesting story off the news:

Grapefruit diet almost cost woman her leg

PARIS, April 3, 2009 (AFP) - A woman who ate a grapefruit each day almost had to have her leg amputated because of a dangerous blood clot, according to an unusual case study reported in the Lancet.

Emergency doctors in Olympia, in the US Pacific coast state of Washington, treated the 42-year-old woman in November 2008 after she was admitted with shortness of breath, dizziness and difficulty walking. An ultrasound scan found she had a large clot blocking the veins of her left leg.

She was in imminent danger of losing the limb to gangrene, but doctors administered a clot-busting drug directly into the blockage and safely dissolved it.

The physicians found she had taken a relatively long car journey, of about an hour and a half, the day before; took a daily dose of oestrogen oral contraceptives; and had a genetic variant, called the factor V Leiden mutation, which is linked to a blood-clot disorder.

All are well-established factors for causing deep vein thrombosis (DVT), as these dangerous events are called.

But what "may well have tipped the balance" is that she had been eating a grapefruit every morning under a weight-loss diet begun three days earlier, the report said.

Grapefruit juice is known to block the action of an enzyme called CYP3A4 which breaks down the contraceptive hormone oestrogen.

This in turn boosts levels of coagulability - the tendency of blood to clot.

Grapefruit juice is broken down only very slowly, which means that it has a cumulative effect if taken daily. Thus, on the third day of her diet, the patient's oestrogen levels would have been many times above normal, helping the clot to form.

DVT has been popularly termed "economy-class syndrome," as it is associated with passengers hunched up on cramped seats in long-haul flights.

But experts say DVT can be inflicted by any kind of immobility - in cars, the office or at home - that causes the leg to be bent for long periods and prevents blood from flowing. The clotting risk is amplified by oral contraceptives and heritability.

Transporters in erythrocytes

Here's something to think about.

The erythrocyte is unique among cells because it lacks a nucleus. At some point in its development, it jetisons the nucleus and and other organelles including mitochondria and lives out the rest of its lifespan circulating as a membrane enclosed sac of haemoglobin and various enzymes.

It is an interesting situation because the erythrocyte, despite having no nucleus survives for an estimated 120 days fulfilling some of most important functions in the body. In the course of its work, as it circulates around the body, it is exposed to a wide variety of endogenous and exogenous chemicals.

The question is 'How does the erythrocyte membrane deal with these chemicals?'. More specifically, what transporters are expressed on the erythrocyte membranes, and what role(s) do they play in health, disease and therapeutics?

Genes vs environment

Not an easy topic, but here is an interesting recent guest column by Sandra Aamodt and Sam Wang, in the New York Times discussing the complex interactions between genes and the environment. Although they discuss this from a largely neuropsychiatric perspective the lessons are widely applicable to therapeutics. We have far too many champions of the genetic approach who push ideas that genetic variability underlie everything that determines drug efficacy and toxicity. The underfunded environmental approaches go largely ignored because they use rather unexciting mundane technology, and produce results that tend not to generate patents.

IMO the gene only approach is clearly not valid. The challenge is how to tease out the various gene-environment interactions and to define them clearly so that they can eventually help us optimize our therapeutic regiments.

Boyanese (Baweanese) in Singapore

Here's an interesting aside following from our previous discussions on ear wax and ethnicities.

A casual discussion with a Boyanese lady revealed that she had wet ear wax. Just an interesting association despite n= 1.

The other interesting nugget of information was that apparently the Boyanese do not classify themselves as Malays on their NRIC (National Registration Identify Card). They are either listed as 'Boyanese' or 'Others'. This is of interest because when we are collecting ethnicity/race information for purposes of medical case studies etc, any 'Malay' data may be under-represented.

The Boyanese originate from a small island off the north coast of East Java. It is of interest to us because many Singaporean Malays trace their heritage back to the original Boyanese settlers. Ethnically they are austronesians like the other Malays. If hospital records use NRIC classifications for ethnicity, and if the Boyanese do not classify themselves on the NRIC as Malays, it may be expected the the Malay data from hospital records will not be very representative.

Aldehyde Dehydrogenase polymorphism

We had previously discussed the alcohol dehydrogenase genetic polymorphism, and had pointed out that among the Han Chinese, there is a high frequency of a genetic variant of alcohol dehydrogenase that allowed a faster conversion of ethanol to acetaldehyde. Acetaldehyde is the chemical that is thought to be responsible for not only the unpleasant effects of alcohol consumption (headaches, flushing etc) but is also thought to be the cause of tissue damage.

There is another enzyme that is responsible for the conversion of aldehyde dehydrogenase to acetic acid. This is called aldehyde dehydrogenase (ALDH). ALDH itself is subject to a genetic polymorphism where the genetic variant ALDH2*2 produces a slower enzyme. Among Han Chinese, the frequency of the ALDH2*2 variant is about 30%.

Among Han Chinese therefore, there is a significant number of individuals who will convert alcohol very quickly to acetaldehyde, and then have a slower removal of acetaldehyde. These individuals build up acetaldehyde concentrations in the blood very rapidly after consumption of alcohol. These individuals are the ones we recognize at drinking parties, who turn red very quickly after low consumption of alcohol.

A recent editorial in Human Genomics 3(2) 2009 highlights the risk this polymorphism poses with respect to the development of esophageal cancers.

So, who are the Thais anyway?

I was thinking about this when I was in Khon Kaen.

It is not an easy question to resolve, as despite the Thais now being numerically so much larger than the Khmers, the Khmers were so much more dominant historically because of the Angkorean civilization. The earliest recognition of a Thai entity only surfaced when the Angkor civilization started to decline.

In early prehistory the region was populated by a Mon language speaking people. Who were they? Most likely people of a Sino-Tibetan stock. On top of this was a distinct amount of 'indianization' as evidenced by civilizations like the Dvararati (pre-angkorean). What 'indianization' really means is not clear, and it is not certain if this was a cultural thing or there was actually an influx of Indian genes as had happened in Cambodia (through the Kambujas from India). In any case, during the Angkor period, the region was 'Khmer-ized', so I am sure there was a substantial of genetic admixture. (See 'So, who are the Khmers anyway?')

As the Khmer civilization ebbed, the Thai people emerged as a distinct entity through the Lavo and Sukhothai kingdoms. A large part of this may have resulted from an influx of Southern Chinese people from Yunnan, fleeing the Mongol invasions.

Thailand now does not recognize differnt ethnicities within the country and everyone is regarded as Thai, although unofficially different ethnic groups are apparent. In a very broad sense, indigenous Thais are generally a sino-tibetan people with a variable amount of Indian admixture. There may be some degree of contribution from the austronesian gene pool, especially in Southern Thailand. On top of these are more recent contributions from Southern China.

So how do we regard pharmacogenetic data from Thailand? I think it becomes important for us to evaluate the source of the data. If it is generated in large urban centres, the contribution of Chinese genes is quite substantial. Indigenous Thai data is best seen in studies conducted in rural communities. In Southern Thailand, one must expect a significant amount of similarity to 'Malay' genetics. In the southern provinces, there still remain pockets of negrito peoples.

This is so far my limited understanding of the situation. I may be wrong. But this is how the current understanding appear to leading us. Perhaps there may be others with a better understanding of Thai ethnicity who can share their experiences and understanding with us?

Hardy & Weinberg

The Hardy Weinberg Equilibrium (HWE) is such a fundamental 'law' in Mendellian genetics. Wikipedia has done a fairly good job summarizing so I am just going to shamelessly copy-paste from there. :) Essentially the principle is based on the random pairing of genetic material during mating. In a system where there is true randomness, at 'steady state' the genotypic frequencies are in 'equilibrium' and will remain relatively stable year after year. In pharmacogenetics, when we are looking at population frequencies of genetic variants, it is always useful to establish if the observed frequencies are consistent with the HWE.

From Wikipedia:
In the simplest case of a single locus with two alleles: the dominant allele is denoted A and the recessive a and their frequencies are denoted by p and q; freq(A) = p; freq(a) = q; p + q = 1. If the population is in equilibrium, then we will have freq(AA) = p² for the AA homozygotes in the population, freq(aa) = q² for the aa homozygotes, and freq(Aa) = 2pq for the heterozygotes.


The HWE is named after G. H. Hardy and Wilhelm Weinberg.

From Wikipedia:

Mendelian genetics were rediscovered in 1900. However, it remained somewhat controversial for several years as it was not then known how it could cause continuous characteristics. Udny Yule (1902) argued against Mendelism because he thought that dominant alleles would increase in the population. The American William E. Castle (1903) showed that without selection, the genotype frequencies would remain stable. Karl Pearson (1903) found one equilibrium position with values of p = q = 0.5. Reginald Punnett, unable to counter Yule's point, introduced the problem to G. H. Hardy, a British mathematician, with whom he played cricket. Hardy was a pure mathematician and held applied mathematics in some contempt; his view of biologists' use of mathematics comes across in his 1908 paper where he describes this as "very simple".

To the Editor of Science: I am reluctant to intrude in a discussion concerning matters of which I have no expert knowledge, and I should have expected the very simple point which I wish to make to have been familiar to biologists. However, some remarks of Mr. Udny Yule, to which Mr. R. C. Punnett has called my attention, suggest that it may still be worth making...

Suppose that Aa is a pair of Mendelian characters, A being dominant, and that in any given generation the number of pure dominants (AA), heterozygotes (Aa), and pure recessives (aa) are as p:2q:r. Finally, suppose that the numbers are fairly large, so that mating may be regarded as random, that the sexes are evenly distributed among the three varieties, and that all are equally fertile. A little mathematics of the multiplication-table type is enough to show that in the next generation the numbers will be as (p+q)²:2(p+q)(q+r):(q+r)², or as p₁:2q₁:r₁, say.

The interesting question is — in what circumstances will this distribution be the same as that in the generation before? It is easy to see that the condition for this is q² = pr. And since q₁² = p₁r₁, whatever the values of p, q, and r may be, the distribution will in any case continue unchanged after the second generation

The principle was thus known as Hardy's law in the English-speaking world until Curt Stern (1943) pointed out that it had first been formulated independently in 1908 by the German physician Wilhelm Weinberg (see Crow 1999). Others have tried to associate Castle's name with the Law because of his work in 1903, but it is only rarely seen as the Hardy–Weinberg–Castle Law.

The Great Ear Wax Poll outcome

We don't know the ethnicity of the pollsters (n=47), nor their country of origin, but with the eye of faith, the outcome shows a nice histogram that is consistent with the Hardy-Weinberg Equilibrium (A=0.73, a=0.27). This is assuming the the three categories represents the three genotypes. This assumption may not be true. Nevertheless the outcome is interesting.

The ABC Transporters

For the longest time we all worked on the premise that drug molecules moved across the cell membranes passively, and by virtue of their lipophilicity. In technical terms, this was determined by the water:octanol partition coefficient. But increasingly we are seeing that this is not all there is to the story. It would seem that few drug molecules actually traverse the lipid bilayer by passive diffusion. Few would cross the membrane without engaging the transport process in some way or other.

One important and very fundamental part of this process is mediated by a superfamily of drug transporters called the ABC transporters. The 'ABC' stands for ATP-Binding Cassette. Apart from having at least one ATP-binding domain, these transporters are characterized by a signature sequence of amino acid residues within the nucleotide binding domain - an LSGGQ motif.

In contrast to prokaryotes, the ABC transporters function as efflux pumps, which together with the detoxification enzymes constitute a complex integrated 'chemo-immunological defense' system against drugs and other xenobiotics.

In human beings, this superfamily of transporters comprises 48 members grouped into 7 families. Just how fundamental these transporters is evidenced by the ubiquity in all living systems be they eukaryotes or prokaryotes. Even mitochondria carry at least 4 of their own ABC transporters.

Prokaryotes
Agrobacterium tumefaciens - 135
Fungi/yeast
Saccharomyces cerevisiae - 22
Plasmodium - 15
Mitochondria - 4
Human - 48

The ABC transporters and their SLC (solute carrier) counterparts are fast shaping up to be probably the most important determinants of interindividual differences in drug efficacy/toxicity.

31st Pharmacological and Therapeutic Society of Thailand Meeting

I just spent 3 wonderful days in Khon Kaen, Thailand at the 31st Pharmacological and Therapeutic Society of Thailand Meeting. I was there as the honoured guest of the Society to deliver the 'Chiravat Sadavongvivad Memorial Lecture was on " The ABC Transporters: Their role in determining drug resistance and drug response'. The proceedings are published in the Thai Journal of Pharmacology. For Khon Kaen University, see here.

Apart from enjoying the characteristically warm and wonderful hospitality of the hosts, it was a great time to catch up with old friendships and also on an academic front, to try and understand a bit more about Thai ideas of ethnicity issues.

ABCC11 Transporter

The ABCC11 gene encodes for a little known member of the ABC (ATP binding cassette) superfamily of membrane transporters. The protein is called MRP8 or multi-drug resistance protein 8. Not much is yet known about its function. It became 'famous' largely because of its association with the dry-wet ear wax phenotype. Additionally, it has been shown to transport cyclic nucleotides e.g. cAMP and cGMP, and consequently has been implicated in resistance to a number of nucleotidic anticancer drugs used for breast cancers.

Other interesting associations other than ear wax....is the association with the production of colustrum by nursing mothers (early milk).

The main genetic polymorphism associated with ABCC11 is the 538G-A transition in exon 4 giving rise to a substitution of glycine to arginine. The frequency of this polymorphism is unknown among our local ethnic groups is Singapore.

What's with the Japanese - wet or dry ear wax??

Another interesting bit of trivia I discovered when I visited RIKEN. There is a genetic polymorphism affecting the ABC (ATP-Binding Cassette) transporter ABC11, that determines if your ear wax comes out dry or wet. This was discovered by Yoshiura et al in 2006. See also report in the New York Times. Apparently the Japanese and Koreans (and Northern Chinese) exclusively have the 'dry ear wax' variant while African and West Europeans have the "wet ear wax" phenotype. The rest of the world have mixed proportions of dry and wet waxes. In Southern China and South East Asia, the frequency of wet wax increases. It is thought that the dry wax allele originated in Northern Asia, thus giving rise to an exclusive distribution of the allele in North China, Korea and Japan.

Wet is black, dry is white

The Japanese use the dry wax phenotype to distinguish the Yamato Japanese from the other Japanese arising from Hokkaido (Ainus) and Ryukyu (Okinawans).

Why not take the ear wax poll?

Who are the Japanese, anyway?

The Japanese ethnic group is deceptively homogeneous.The dominant ethnic group however is recognizable as the Yamato people. These are whom we have come to commonly recognize as 'Japanese'. However, some minor ethnic groups do find their home in Japan. Apart from the obvious transplants such as Koreans, Chinese, Taiwanese etc, these are the Ainus, Ryukyuans and the Nivkhs.

The Yamatos are people who derive originally from the North Chinese mainland, having crossed over through the Korean peninsula. Consequently, there is a genetic thread that runs through and links the Northern Han Chinese and Koreans with the Yamato Japanese. By contrast the Ainu and Ryukyuans are earlier peoples who antedate the arrival of the Yamato people. RIKEN has data that show the genetic similarity between the Ainu and the Ryukuans (Okinawans). It is thought that the arrival of Yamato cleaved the distribution of the original Austronesian population to create a northern Ainu group and a southern Okinawan group. The Nivkhs are a small minority who derive from Siberia.

That said, the Japanese are pretty much of the Yamato group (>98% of toal 130 million). The Ryukuans probably account for about 1% and the Ainu even less (0.3%).

From a practical perspective, when one examines Japanese PGx data we should make mental links with data originating from Northern China and Korea. Accordingly, some caution is necessary when we try and connect the dots between Japanese and essentially Southern Chinese and South East Asian data.

The following excerpted from Wikipedia (Japanese_people):

A recent study for the origins of Japanese people is based on the "dual structure model" proposed by Hanihara in 1991. He concludes that modern Japanese lineages consist of the original Jōmon people and immigrants from the Yayoi period. The Jōmon people originated in southeast Asia, moving to the Japanese Archipelago in the Palaeolithic period. In past several decades, the Japanese people was proposed to relate to Yi, Hani and Dai people based on folk customs or genetic evidences.

Another southeast Asian group moved to northeastern Asia. The population of this group increased in the Neolithic period and some moved to the archipelago during the Yayoi period. The miscegenation prevailed in Kyūshū, Shikoku and Honshū islands but not in Okinawa and Hokkaido, respectively represented by the Ryukyuan and Ainu people. This theory was based on the study of the development of human bones and teeth. The comparison of mitochondrial DNA between Jōmon people and medieval Ainu also supports the theory.

Personalized medicine vs Genome-based medicine

I have a very good series of meeting as part of the Health Sciences Authority, Singapore (HSA) team with the Japanese Pharmaceutical and Medical Devices Agency (PMDA), Ministry of Health, Labour and Welfare (MHLW), and the National Institute of Health Sciences (NIHS), as well as the RIKEN Center for Genomics Medicine (CGM).

I learnt a lot just talking the the various agencies. But the highlight for the meeting for me was catching that fleeting comment by Prof Yusuke Nakamura, Director of Riken CGM, that there was a difference between "personalized medicine" and genome-based medicine", and that RIKEN had more of a focus on "genome-based medicine". I thought that was incredibly insightful. So many of the luminaries in PGx toss around the term "personalized medicine" almost as a justification for spending their multimillion $$ budgets but totally missing the point that what they are after really isn't personalizing therapeutics.

In our analogy of the F1 race car driver, it's really no different from developing better and more precise fuel injection systems, or tires that are better suited for the road surface. Technology is great. But after all that we musn't forget that one still needs to navigate and drive fast to get to the finish line, ... with the best time. That is personalized medicine.

See recent editorial: Personalized medicine: are we there yet?

Pharmacogenetics / Pharmacogenomics

Here's an interesting observation I made while preparing for a presentation. This is a plot of the yearly publications where you can find the term "Pharmacogenetics" or "Pharmacogenomics". This is obtained by just searching via SCOPUS using those keywords.

"Pharmacogenetics" had a steady hit rate of about 50-60 before 1995, and publications took off after that on a steady incline. The word "Pharmacogenomics" was first used in 1997, and then really kicked in after 1999. But what really surprised me was that, unlike "Pharmacogenetics", the hit rate has since plateaued off after 4-5 years.

I am not too sure what the reason is, but I suspect there may be a bit of "Pharmacogenomics" fatigue, and the genomics people moving into broader areas of "Genomics", have stopped using the term "Pharmacogenomics". The "Pharmacogenomics" people by contrast, have tended to remain faithful to their cause and the science continues to expand.

Ethanol pharmacokinetics

Ethanol is a small molecule that has a strong affinity for water. It is absorbed efficiently and rapidly after consumption. Regardless of how it is consumed and in what form of spirits, the effect of alcohol on the central nervous system is closely correlated with the circulating concentrations of alcohol in the blood. This allows enforcement authorities to set certain tolerable (legal) limits of blood alcohol concentrations (BAC) as a surrogate limit for alcoholic intoxication (Singapore's legal limit is 0.08%, or 80 milligrams of alcohol per 100 millitres of blood). As the alcohol in the blood equilibrates very rapidly with the alveolar concentrations, breath alcohol concentrations (BrAC) are often used by the traffic police as an alternative to measuring blood alcohol concentrations. In Singapore, the BrAC limit is 35 micrograms of alcohol per 100 millilitres of breath. See Singapore Traffic Police.

It is therefore of some interest to the public to know how much alcohol one can drink without exceeding the BrAC limits.

The peak (maximum) BrAC after consuming alcohol depends on a number of factors:

a] the total amount of alcohol consumed (not the volume of beverage). Obviously the larger the quantum of alcohol, the higher the BAC will be.

b] the rate of absorption of the alcohol. The rate will be faster if the stomach is empty, and if the concentrations are high but not too high. Higher concentrations of spirit (alcohol) will produce a greater concentration gradient to drive the absorption. However, if the concentrations are too high, there may be slower gastric emptying of stomach contents into the small intestines where absorption of the alcohol is faster and more complete. Men theoretically therefore absorb more alcohol then women.

c] the amount of first pass metabolism in the linings of the stomach. There is some controvery about how important this actually is. Women are said to have less alcohol dehydrogenase expressed in the stomach walls and therefore have less first pass metabolism. The less metabolism, the greater the absorption.

d] the 'volume of the body' into which the alcohol is distributed. Pharmacokinetically this is referred to as the volume of distribution. Men have a higher water content in their body compared to women, and since alcohol is distributed primarily into body water, men will weight for weight, develop lower BrACs.

e] the rate of elimination of alcohol. The ADH genetic polymorphims have been discussed elsewhere. If consumed quickly, the rate of elimination will not affect the BrAC much, but if the consumption is protracted over a period of time, long enough for elimination to occur, the rate of elimination may have a significant effect on the BrAC.

Based on the above understanding, it is a reasonable expectation (assuming that the amount of alcohol consumed is exactly the same) that a muscular Chinese man sipping several glasses of wine over the course of a 4-course meal will produce substantially lower BrACs compared to an Indian lady quaffing down a series of stiff drinks on an empty stomach.

Alcohol and the breathalyzer #1

The question is: Given the genetic polymorphism affecting alcohol dehydrogenase (ADH), how much variability is there in the population, and how does this variability affect the amount of alcohol that can be consumed before one exceeds the breathalyzer legal limits?

Today we begin a study at Changi General Hospital to find out.

Keep watching this space. We'll have the results out soon....

The Great Durian Poll outcome

Many thanks to all who participated. We managed a half decent 66 responses... :).

I must say I was somewhat surprised by the results. As a non-durian lover I was expecting to see a much clearer separation of lovers and haters, with perhaps a more distinct bimodality in the distribution, somewhat like the taster/non-taster distribution. Instead we had a kind of log-normal distribution, like the CYP3A4/5 one.

There are a couple of possible reasons for this. One is that there may be a sampling bias, i.e. non-durian lovers aren't that motivated to participate. Secondly, the category axis is an ordinal scale, so even though I tried to space out the responses as 'equally' as I can imagine them to be, there is no certainty that the categories have equal intervals. It could well be that there is a larger separation at the "So-so only....no big deal" category.

In any case, it was an interesting exercise. As has been shown many times before, the lack of a clear 'bi- or poly-modal' distribution does not necessarily exclude any genetic bases for the interindividual differences.

Regardless of the genetic or lack of genetic basis for the interindividual difference, (and assuming the sample represents all of Singapore) there is an interesting lesson for us here...

Firstly, because of the preponderance of durian lovers in the sample, one can say Singaporeans generally love durians...passionately...though they can mostly live without it. Secondly and perhaps more importantly, is to recognize that despite such an overwhelming support for the spikey fruit, there are regulations that protect the interests of the people represented by right tail of the distribution. You don't allow the fruit on airplanes, in cars, shopping centres and restaurents. It is such a common sense thing to do, so we kinda take it for granted. It is actually a very common phenomenon. In a classroom, for example, the (good) teacher's attention is often focused on the poor students, or the bright spark...and not on the majority of the students who (on average) do not have any problems.

We have the same situation in dealing with therapeutic problems. Most dosage regimens are designed for the average patient (central tendency, remember?), and we know (or should know) that the patients who develop problems are those at the tails of the distribution...either inadequate response, or too much response/toxicity. Our mental focus should really be on helping the patients in the tails of distribution achieve an appropriate therapeutic response. Yet physicians often forget this and assume that the recommended (average) dose will meet the needs of all the patients they treat.

The challenge for us is in helping physicians identify which of the patients reside in the tails. This is where pharmacogenetics come in.

There is a nice review, "Pharmacogenetics - Tailoring Treatment for the Outliers" in the New England Journal of Medicine by Woodcock and Lesko that deals with this specific issue. It also reminds us of what Sir William Osler had shared over a hundred years ago: "If it were not for the great variability among individuals, medicine might as well be a science and not an art." Paradoxically, medicine is now at a stage of development where dealing with this variability has become much more of a science.

Alcohol pharmacogenetics in Singapore

The news about the alcohol related death at the National University of Singapore triggered some thinking about the interesting aspects about how alcohol (ethanol) is handled by the Chinese in Singapore.

Ethanol regardless of the form it comes in, is metabolized fairly efficiently in the body by means of an enzyme, alcohol hydrogenase (ADH). Although there are other enzymes that can also do this (e.g. CYP2E1), the most important pathway for alcohol degradation is really ADH. ADH itself is encoded by 7 genes but the major enzyme in the stomach mucosa and liver is the Class 1 enzyme, encoded by the ADH1B gene.

CH₃CH₂OH + NAD⁺ → CH₃CHO + NADH + H⁺

What is important for us to realize is that there is a common genetic polymorphism affecting the ADHB1 gene in Chinese. An 'atypical' ADH was first described in 1968 by Von Wartburg and Schuerch (Ann. N.Y. Acad. Sci. 151: 936-947, 1968). Subsequently Stamatoyannopoulos in 1975 found the atypical variant in 85% of Japanese. The variant is now identified as ADH1B*47 (previously ADH2*2) and exchanges a histidine for arginine in the protein, resulting in an enzyme with very much enhanced activity (100 fold difference in Vmax). A recent study (Alcohol Clin Exp Res. 2004 Jan;28(1):10-4) in Jewish carriers of this variant showed increased rate of elimination of alcohol from the blood (8.09 vs 7.14 g/hr).

This genetic variant is particularly common in South East and East Asia and is an important genetic 'protector' against alcoholism because it is thought to result in more unpleasant outcomes because of higher levels of aldehyde production . The frequency among Taiwanese Han Chinese is about 75% (Hepatology. 1997 Jan;25(1):112-7 ).

A recent report was able to show this global distribution of ALD1B*47 variant (Am J Hum Genet. 2007 Oct;81(4):842-6. Epub 2007 Aug 24). Note the interesting cluster in West Asia. Also the absence of this variant in the Indian subcontinent. More about this later, and its implications for us in Singapore.

Global contour plot of the ADH1B*47His allele frequency

Pharmacogenetics (PGt) vs Pharmacogenomics (PGx)

Pharmacogenetics isn't really a new science. The term was first coined by Friedrich Vogel back in 1959 when not many people were really interested. It was really only in relatively recent time, after genetic/genomic technologies became widely available that it had a renaisance. Now it's become somewhat of a hip and much hyped up science.

Newbies often get confused by the two terms 'pharmacogenetics' and 'pharmacogenomics', often abbreviated to PGt and PGx. The two terms have overlapping characteristics and PGt is often seen nowadays as being a subset of PGx. In fact the two terms have often been used interchangeably by various publications. But for those of us working in this areas, the distinctions can be quite distinct. For us, PGt is often a study of the variations in a targeted gene, or group of functionally related genes. PGx, on the other hand is a much broader investigation of genetic variations at the level of the genome.

Here are some definitions of these terms as given by the FDA and the NCBI.

FDA Guidance for Industry (2008) E15...
PGt: The study of variations in DNA sequence as related to drug response
PGx: The study of variations of DNA and RNA characteristics as related to drug response

NCBI Factsheet
PGt: The study of inherited differences (variation) in drug metabolism and response.
PGx: The general study of all of the many different genes that determine drug behavior.

Rat poison and the F1 driver - the warfarin story

The anticoagulant warfarin actually started life as rat poison. Chemically, it is derived from a natural plant product, coumarin. The way it acts is by inhibiting the enzyme Vitamin K epoxide reductase, and in so doing reduce formation of various Vit K dependent clotting factors.

So what's the deal about F1 drivers?

Well... like F1 drivers, the physician using warfarin needs to keep his eye on the road. Too little warfarin, and there is inadequate therapeutic anticoagulation; too much warfarin and the patient may suffer a catastrophic bleed. Fortunately, he has a way to do this. The Prothrombin Time and other derived measures such as the International Normalized Ratio (INR) provide a heads up to the physician about how much anticoagulation has been provided for the patient. By keeping his eye on the INR, the physician can adjust the dose of warfarin to provide just the right range on anticoagulation the patient needs. This is important, because the warfarin requirements for every patient differ, and the warfarin dose needs to be 'individualized'.

More recently, various other biomarkers enable the physician to make educated guesses about the dosage requirement for the patient. These are genetic markers related to the rate of metabolic degradation of warfarin through cytochrome P450 2C9 (not many such problems in our Chinese population) and the genetically reduced sensitivity of the Vitamin K epoxide reductase C1 subunit (VKORC1). However, using these genetic biomarkers only provide an improved starting dose. Once the race car engine starts, the F1 driver will still have to manage the therapeutic process through keeping a close eye on the INR.

There have been many discussions about the genotyping of patients prior to dosing with warfarin. I have no doubt to its usefulness in helping us to understand the patient a lot better. But becasue there is already a good efficacy marker (the INR) for us to titrate the patients dosing against, the improved starting point may only be of theoretical benefit. I think most of the benefit will come in situations when you need to deliver very fast anticoagulation. Where time is not on an essence, genotyping would likely not be a cost effective option.

Therapeutics and the F1 race.....

There are quite a few variables operating in the context of an F1 race. Where the driver is concerned there are questions about his mental alertness, situational awareness, speed of reflexes, knowledge, experience and even his risk for appetite. Clearly there are also variables related to machine performance and conditions affecting road and track. All this variability create exciting conditions and an unpredictable outcome. Yet, no matter who wins eventually, most car-machine partnerships perform outstanding well.

The operation of any high performance machine system requires complex and sophisticated servo-systems operating at multiple levels. At its most simplistic level, the race car driver need to sense the speed of the car and adjust the speed through an interplay of acceleration and deceleration.

Precision therapeutics is really not any different. The physician must be able to recognize the effect of his procedures (drug regiment) and modulate these through the adjustment of his procedures (drugs dosages, for example). What is surprising is how many physicians do not recognize that they need to do this. They function like race car drivers who don't know their car, have no speedometer and are blinded. What's worse....don't even know they have brake and accelerator pedals.

For them, the patient is represented by a virtual description of a population average. Their expectation of a therapeutic effect is a relatively crude measurement of eventual outcome - cured, didn't work...died(often they don't even recognize they are driving blind). And they don't seem to realize, they can actually adjust drug doses in scientifically rational ways.

We can actually do a whole lot better than that. And many physicians have.

It's good to blog - Nature Editorial

Reprinted here is an Editorial from Nature about researchers blogging.I am smugly pleased I started before they said it ......

Editorial
Nature 457, 1058 (26 February 2009) | Published online 25 February 2009

It's good to blog

More researchers should engage with the blogosphere, including authors of papers in press.

Is blogging a part of science, journalism or public discourse? In fact it may be all of these — an ambiguity that can sometimes leave scientists feeling uncertain about the rules of the game.

Imagine, for example, a case in which Nature's blog The Great Beyond highlights new scientific results presented at a conference on climate. That blog entry then stimulates an online debate, with climate sceptics interpreting the results their way, and others firing off rebuttals. Imagine also that the work is described in a paper that had been accepted, but not published, by Nature. The authors of the paper want to enter the fray, but feel inhibited from doing so because of the embargo imposed by Nature and many other journals on communication by authors to the media ahead of publication. And why was Nature blogging their work anyway, ahead of its publication?

This scenario highlights a need for clarification about Nature publications' procedures, and about how embargoes apply to blogs. It also highlights more generally the potential importance of scientists engaging in the blogosphere.

All Nature journals maintain confidentiality about submitted papers, so that only the editors directly responsible for those papers know about them. Other staff — including the various publications' journalists — are usually informed about a paper only once it has been accepted, and with the proviso that they do not disseminate any information about it to external contacts or readers. Likewise, we ask that authors refrain from actively promoting their work to the media and public ahead of its publication. This embargo policy rests on the principle that scientists' and the public's best interests are served by press coverage of work that has been peer reviewed, and is available for others to see for themselves.

At the same time, however, our cardinal rule has always been to promote scientific communication. We have therefore never sought to prevent scientists from presenting their work at conferences, or from depositing first drafts of submitted papers on preprint servers. So if Nature journalists or those from any other publication should hear results presented at a meeting, or find them on a preprint server, the findings are fair game for coverage — even if that coverage is ahead of the paper's publication. This is not considered a breaking of Nature's embargo. Nor is it a violation if scientists respond to journalists' queries in ensuring that the facts are correct — so long as they don't actively promote media coverage.

The blogosphere differs from mass media and specialized media in many respects, but the same considerations apply in disseminating new scientific results there. Authors of papers in press have the right to correct misrepresentations and to point to results that will appear in a paper. But a full discussion should await the paper's publication.

Indeed, researchers would do well to blog more than they do. The experience of journals such as Cell and PLoS ONE, which allow people to comment on papers online, suggests that researchers are very reluctant to engage in such forums. But the blogosphere tends to be less inhibited, and technical discussions there seem likely to increase.

Moreover, there are societal debates that have much to gain from the uncensored voices of researchers. A good blogging website consumes much of the spare time of the one or several fully committed scientists that write and moderate it. But it can make a difference to the quality and integrity of public discussion.

Durian lovers vs durian haters

Here's a slight frivolous post inspired by tonight's after dinner conversation.

The durian (Durio zibethinus), reckoned by many as the king of fruits in Asia. Others have less flattering descriptions. It's a fruit that you either love or hate.

Some descriptions of its taste (shamelessly plagiarized from Wikipedia):
Writing in 1856, the British naturalist Alfred Russel Wallace provides a much-quoted description of the flavour of the durian:
“The five cells are silky-white within, and are filled with a mass of firm, cream-coloured pulp, containing about three seeds each. This pulp is the edible part, and its consistence and flavour are indescribable. A rich custard highly flavoured with almonds gives the best general idea of it, but there are occasional wafts of flavour that call to mind cream-cheese, onion-sauce, sherry-wine, and other incongruous dishes. Then there is a rich glutinous smoothness in the pulp which nothing else possesses, but which adds to its delicacy. It is neither acid nor sweet nor juicy; yet it wants neither of these qualities, for it is in itself perfect. It produces no nausea or other bad effect, and the more you eat of it the less you feel inclined to stop. In fact, to eat Durians is a new sensation worth a voyage to the East to experience. ... as producing a food of the most exquisite flavour it is unsurpassed.”

While Wallace cautions that "the smell of the ripe fruit is certainly at first disagreeable", later descriptions by westerners are more graphic. British novelist Anthony Burgess writes that eating durian is "like eating sweet raspberry blancmange in the lavatory." Chef Andrew Zimmern compares the taste to "completely rotten, mushy onions." Anthony Bourdain, while a lover of durian, relates his encounter with the fruit as thus: "Its taste can only be described as...indescribable, something you will either love or despise. ...Your breath will smell as if you'd been French-kissing your dead grandmother." Travel and food writer Richard Sterling says:

“... its odor is best described as pig-shit, turpentine and onions, garnished with a gym sock. It can be smelled from yards away. Despite its great local popularity, the raw fruit is forbidden from some establishments such as hotels, subways and airports, including public transportation in Southeast Asia.

Other comparisons have been made with the civet, sewage, stale vomit, skunk spray and used surgical swabs.

There are clear indications that this is a pharmacogenetic differentiation of durian lovers from haters, though I do not know of any study to this effect.

Go ahead and take the Great Durian Poll!!

The not so normal distribution

The normal distribution is a convenient tool when you need to describe your data. Unfortunately it introduces a blind spot when it comes to interpreting the data.

When we look at the distribution, our eye intuitively focuses on the centre of the distribution. We see the central tendency of the distribution and the variance around it. This is fine when you are describing the data. But averages don't really help you if you are the storeman who's responsible for purchasing clothes for a bunch of factory workers.

This is the odd thing about studying variability in therapeutic response to drugs. We all know variability exists. We see this in every sphere of human activity, from buying clothes and cosmetics to the ability to complete a physical fitness test. Yet inexplicably, when it comes to dosing patients, people imagine that a dosage regiment based on the mean of a relatively small unrepresentative study sample will somehow represent the dosage requirement for everyone on this planet.

Here is a series of distributions of the clearances of CYP3A5 substrates midazolam and alfentanil (Kharasch et al, Clinical Pharmacology & Therapeutics (2007) 82, 410–426). The distributions are skewed to the right and so are clearly log-normally distributed.

Here is a frequency distribution of the log-metabolic ratio for midazolam in a Chinese population (Zhu et al, Br J Clin Pharmacol. 2003 March; 55(3): 264–269).

Notice from these plots just how variable the clearances and the metabolic ratios (more about this later) are. How do we, under these conditions determine the correct doses for each patient? Clearly applying population averages will not work. Are we able to do it?

The earlier posting on wafarin show how it can be done for warfarin.More on dosage optimization issues later.

Highlighted report: Validation of VKORC1 and CYP2C9 genotypes on interindividual warfarin maintenance dose

Validation of VKORC1 and CYP2C9 genotypes on interindividual warfarin maintenance dose: a prospective study in Chinese patients.

Huang, Sheng-Wen, Chen, Hai-Sheng, Wang, Xian-Qun, Huang, Ling, Xu, Ding-Li, Hu, Xiao-Jia, Huang, Zhi-Hui, He, Yong, Chen, Kai-Ming, Xiang, Dao-Kang, Zou, Xiao-Ming, Li, Qiang, Ma, Li-Qin, Wang, Hao-Fei, Chen, Bao-Lin, Li, Liang, Jia, Yan-Kai, Xu, Xiang-Min

Objectives: To develop a warfarin-dosing algorithm that could be combined with pharmacogenomic and demographic factors, and to evaluate its effectiveness in a randomized prospective controlled clinical trial.

Methods: A pharmacogenetics-based dosing model was derived using retrospective data from 266 Chinese patients and multiple linear regression analysis. To prospectively validate this model, 156 patients with an operation of heart valve replacement were enrolled and randomly assigned to the group of pharmacogenetics-guided or traditional dosing for warfarin therapy. All patients were followed up for 50 days after initiation of warfarin therapy. The log-rank test was compared with the time-to-event (Kaplan-Meier) curves. Cox proportional hazards-regression model was used to assess the hazard ratio of the time to reach stable dose.

Results: The linear regression model derived from the pharmacogenomic model correlated with 54.1% of warfarin dosing variance. The final multiple linear regression model included age, body surface area, VKORC1, and CYP2C9 genotype. The study showed that the hazard ratio for the time to reach stable dose was 1.932 for the traditional dosing group versus the model-based group and a close and highly significant relationship was observed to exist between the predicted and the actual warfarin dose (R2=0.454).

Conclusion: A pharmacogenetics-based dosing algorithm has been developed for improvement in the time to reach the stable dosing of warfarin. This model may be useful in helping the clinicians to prescribe warfarin with greater safety and efficiency.

See also:

Estimation of the Warfarin Dose with Clinical and Pharmacogenetic Data.
The International Warfarin Pharmacogenetics Consortium.

BACKGROUND: Genetic variability among patients plays an important role in determining the dose of warfarin that should be used when oral anticoagulation is initiated, but practical methods of using genetic information have not been evaluated in a diverse and large population. We developed and used an algorithm for estimating the appropriate warfarin dose that is based on both clinical and genetic data from a broad population base. METHODS: Clinical and genetic data from 4043 patients were used to create a dose algorithm that was based on clinical variables only and an algorithm in which genetic information was added to the clinical variables. In a validation cohort of 1009 subjects, we evaluated the potential clinical value of each algorithm by calculating the percentage of patients whose predicted dose of warfarin was within 20% of the actual stable therapeutic dose; we also evaluated other clinically relevant indicators. RESULTS: In the validation cohort, the pharmacogenetic algorithm accurately identified larger proportions of patients who required 21 mg of warfarin or less per week and of those who required 49 mg or more per week to achieve the target international normalized ratio than did the clinical algorithm (49.4% vs. 33.3%, P<0.001,>/=49 mg per week). CONCLUSIONS: The use of a pharmacogenetic algorithm for estimating the appropriate initial dose of warfarin produces recommendations that are significantly closer to the required stable therapeutic dose than those derived from a clinical algorithm or a fixed-dose approach. The greatest benefits were observed in the 46.2% of the population that required 21 mg or less of warfarin per week or 49 mg or more per week for therapeutic anticoagulation.

Cost-effectiveness of using pharmacogenetic information in warfarin dosing for patients with nonvalvular atrial fibrillation.
Eckman MH, Rosand J, Greenberg SM, Gage BF.
University of Cincinnati Medical Center, Cincinnati, OH 45267-0535, USA. mark.eckman@uc.edu

BACKGROUND: Variants in genes involved in warfarin metabolism and sensitivity affect individual warfarin requirements and the risk for bleeding. Testing for these variant alleles might allow more personalized dosing of warfarin during the induction phase. In 2007, the U.S. Food and Drug Administration changed the labeling for warfarin (Coumadin, Bristol-Myers Squibb, Princeton, New Jersey), suggesting that clinicians consider genetic testing before initiating therapy. OBJECTIVE: To examine the cost-effectiveness of genotype-guided dosing versus standard induction of warfarin therapy for patients with nonvalvular atrial fibrillation. DESIGN: Markov state transition decision model. DATA SOURCES: MEDLINE searches and bibliographies from relevant articles of literature published in English. TARGET POPULATION: Outpatients or inpatients requiring initiation of warfarin therapy. The base case was a man age 69 years with newly diagnosed nonvalvular atrial fibrillation and no contraindications to warfarin therapy. TIME HORIZON: Lifetime. PERSPECTIVE: Societal. INTERVENTION: Genotype-guided dosing consisting of genotyping for CYP2C9*2, CYP2C9*3, and/or VKORC1 versus standard warfarin induction. OUTCOME MEASURES: Effectiveness was measured in quality-adjusted life-years (QALYs), and costs were in 2007 U.S. dollars. RESULTS: In the base case, genotype-guided dosing resulted in better outcomes, but at a relatively high cost. Overall, the marginal cost-effectiveness of testing exceeded $170 000 per QALY. On the basis of current data and cost of testing (about $400), there is only a 10% chance that genotype-guided dosing is likely to be cost-effective (that is, <$50 000 per QALY). Sensitivity analyses revealed that for genetic testing to cost less than $50 000 per QALY, it would have to be restricted to patients at high risk for hemorrhage or meet the following optimistic criteria: prevent greater than 32% of major bleeding events, be available within 24 hours, and cost less than $200. LIMITATION: Few published studies describe the effect of genotype-guided dosing on major bleeding events, and although these studies show a trend toward decreased bleeding, the results are not statistically significant. CONCLUSION: Warfarin-related genotyping is unlikely to be cost-effective for typical patients with nonvalvular atrial fibrillation, but may be cost-effective in patients at high risk for hemorrhage who are starting warfarin therapy.